3DFAACTS-SNP: using regulatory T cell-specific epigenomics data to uncover candidate mechanisms of type 1 diabetes (T1D) risk.

ABSTRACT:

Background

Genome-wide association studies (GWAS) have enabled the discovery of single nucleotide polymorphisms (SNPs) that are significantly associated with many autoimmune diseases including type 1 diabetes (T1D). However, many of the identified variants lie in non-coding regions, limiting the identification of mechanisms that contribute to autoimmune disease progression. To address this problem, we developed a variant filtering workflow called 3DFAACTS-SNP to link genetic variants to target genes in a cell-specific manner. Here, we use 3DFAACTS-SNP to identify candidate SNPs and target genes associated with the loss of immune tolerance in regulatory T cells (Treg) in T1D.

Results

Using 3DFAACTS-SNP, we identified from a list of 1228 previously fine-mapped variants, 36 SNP

SUBMITTER: Liu N 

PROVIDER: S-EPMC9244893 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature